Color is a property of light that depends on wavelength. When light falls on an object, some of it is absorbed and some is reflected. The apparent color of an opaque object depends on the wavelength of the light that it reflects; e.g., a red object observed in daylight appears red because it reflects only the waves producing red light. The color of a transparent object is determined by the wavelength of the light transmitted by it. An opaque object that reflects all wavelengths appears white; one that absorbs all wavelengths appears black. Therefore, black is said to result from the absence of color, and white from the presence of all colors mixed together.
Colors whose beams of light in various combinations can produce any of the color sensations are called primary, or spectral, colors. The process of combining these colors is said to be “additive,” i.e., the sensations produced by different wavelengths of light are added together. The additive primaries are red, green, and blue-violet. White can be produced by combining all three primary colors.
FIG. 1A is an illustration of a classic RGB color cube. The color cube represents the “additive” property of colors. Each vertex along an axis represents a primary color, i.e., red (x-axis), green (y-axis) and blue (z-axis). Other vertexes of the cube represent the secondary color resulting from the combination of primary colors. For example, a combination of red and green produces yellow, and a combination of all three primary colors produces white.
The scientific description of color involves the specification of all relevant properties of a color either subjectively or objectively. The subjective description gives the hue, saturation, and intensity of a color. Hue refers to what is commonly called color, i.e., red, green, blue-green, orange, etc. Saturation refers to the richness of a hue as compared to a gray of the same brightness. Intensity refers to the lightness or brightness of a color or a gray. A subjective color notation system provides comparison samples of colors rated according to these three properties of hue, saturation and intensity. This system is more intuitive or qualitative where color manipulation is more consistent with how humans perceive and interpret color.
In an objective system for color description, the corresponding properties are described by quantitative factors, such as wavelength, purity and luminance. The objective system is more suitable for describing “color” to and through an inanimate object, such as a computer chip, a television display, or other electronic devices. For instance, in digital imaging, colors can be represented by discrete combinations of red, green and blue (RGB) signals. In some instances, color can be represented by digitized samples of luminance (Y) and two color differences (Cb and Cr), where Y is related to the weighted total of the RGB signals and Cb and Cr represent the scaled and offset color difference signals B-Y and R-Y, respectively.
In video standards for standard-definition (SD) and high-definition (HD) video signal transmission, a video signal is represented by digitized samples of digital luminance, Y, and the color differences, Cb and Cr. The digital luminance and color difference values (Y, Cb, Cr) can be derived from the three primary analog signals representing RGB, i.e., E′R, E′G, and E′B, according to world-wide video standards set forth in ITU-R BT.601 and ITU-R BT.709. Each of the values (Y, Cb, Cr) in the luminance/color differences color space is a function of all three primary analog values in the other (R, G, B) color space.
Typically, a digital color video signal transmitted in a luminance/color differences format, such as (Y, Cb, Cr), is converted to the (R, G, B) format by a receiving device so that the signal can be displayed by the device. Because of the interrelated nature of the variables, i.e., each variable in either color space is a function of all three variables in the other color space, the standard digital video formats, (R, G, B) and (Y, Cb, Cr), can be related by a set of color space conversion formulae. Basically, each variable in either color space can be calculated from all three variables in the other color space after linear transformation, quantization, and offsetting.
It may be desirable to modify the digital video signal somewhere in the transmission and/or reception paths before displaying the signal on the display device. For instance, such modifications can be used to:                correct color hue shift and color saturation distortion during analog transmission and reception of the video signal        compensate for the differences in color gamut, i.e., the extent of the colors that can be displayed, of different display devices utilizing different display technologies, such as cathode-ray tube (CRT), liquid crystal display (LCD), digital micro-mirror device (DMD), and plasma display panel (PDP), in order to achieve consistent displayed color; and        enhance a viewer's viewing experience by displaying color adjusted to the viewer's preferences and tastes.        
Color pixel data in the digital color video signal can be modified directly by digital computation. Because the transmission formats as described above are luminance (Y) and color differences (Cb and Cr), it is desirable to modify the color pixel data in (Y, Cb, Cr) format by digital computation. Digital processing provides several advantages that are appropriate for the processing of digital video signals in the (Y, Cb, Cr) format. For example: (1) the resolution in a digital computation is a function of the level of quantization, so higher resolution of pixel data, which means higher visual quality, can be achieved with higher bit widths for the representation and the computation of pixel data; (2) non-linear and adaptive algorithms that are difficult or impossible to realize in an analog system can be efficiently and reliably implemented in video signal processing units to achieve superior visual quality; and (3) the characteristics of a video signal processing unit can be fine-tuned easily and promptly by programming its coefficients and/or parameters.
Pixel data values in the standard digital video formats, e.g., (Y, Cb, Cr) and (R, G, B), are represented by variables in Cartesian coordinates. While this makes digital processing easier, it is well recognized that the chromatic portion of the pixel data value, e.g., (Cb, Cr), carry less subjective meaning to the way humans perceive and interpret color. In other words, humans tend not to perceive or describe color in color difference value (Cb, Cr) terms. Accordingly, modifying color difference, i.e., Cb, Cr, values is not intuitive to a viewer.
As stated above, humans are receptive to subjectively oriented color space representations, such as hue, saturation, and intensity (HSI). HSI color representations are more intuitive in manipulating color and are more consistent with the way humans perceive and interpret color. The conversion between color differences representation (Cb, Cr) and hue/saturation representation, however, involves trigonometric functions such as sine, cosine, and arc tangent. These trigonometric conversions are time-consuming and/or require expensive computational resources.
Accordingly, it is desirable to provide a method and system for controllably altering the characteristics of a digitally encoded video signal with respect to color hue and color saturation. The method and system should not require extensive computational resources and should be efficient.